王梦雪,
谢显中
1.重庆邮电大学计算机科学与技术学院 重庆 400065
2.重庆邮电大学重庆市计算机网络与通信技术重点实验室 重庆 400065
基金项目:国家自然科学基金 (61601070)，重庆市教委科学技术研究重大项目(KJZD-M201900602)，重庆市教委科学技术研究重点项目(KJZD-K201800603)，重庆市基础研究与前沿探索项目(CSTC2018jcyjAX0432)
详细信息
作者简介:马彬：男，1978年生，教授，主要研究方向为异构无线网络、认知无线电网络等
王梦雪：女，1995年生，硕士生，研究方向为异构无线网络
谢显中：男，1966年生，教授，博士生导师，主要研究方向为无线和移动通信技术
通讯作者:马彬 mab_cqupt@sina.com
中图分类号:TN915计量
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被引次数:0
出版历程
收稿日期:2019-09-29
修回日期:2020-05-29
网络出版日期:2020-07-12
刊出日期:2020-12-08
Handoff Algorithm Based on Location Prediction in Ultra-dense Heterogeneous Wireless Network
Bin MA,,Mengxue WANG,
Xianzhong XIE
1. Institute of Computer Science and Technology, Chongqing University of Post and Telecommunications, Chongqing 400065, China
2. Chongqing Key Laboratory of Computer Network and Communication Technology, Chongqing University of Post and Telecommunications, Chongqing 400065, China
Funds:The National Natural Science Foundation of China (61601070), The Major Project of Science and Technology Research of Chongqing Education Commission (KJZD-M201900602)，The Key Project of Science and Technology Research of Chongqing Education Commission (KJZD-K201800603), The Foundation Research and Advanced Exploration Project of Chongqing (CSTC2018jcyjAX0432)
摘要
摘要:在密集异构蜂窝网络和无线局域网络构成的超密集异构无线网络中, 变速移动的车辆终端会面临更加频繁的切换，导致用户服务质量(QoS)变差。该文针对上述问题，首先，利用高斯马尔可夫移动模型，预测车辆下一时刻的位置，筛选出满足终端服务质量的候选网络集，与当前的候选网络集做交运算，其次，当前接入网络不在交集中，则使用变步长的萤火虫算法寻找最佳网络；再次，对因预测误差导致的切换失效，则把终端用户迁移到宏蜂窝，以保证通信的持续性。仿真结果表明，在超密集异构无线网络中，使用该文所提算法能够减少乒乓切换等频繁切换现象，同时，提升了用户的服务质量和网络吞吐量。
关键词:超密集异构网络/
切换/
服务质量/
位置预测
Abstract:In the ultra-dense heterogeneous wireless network composed of heterogeneous cellular networks and wireless local area networks, vehicle terminals with variable speeds will face more frequent handovers, resulting in the deterioration of user’s Quality of Service (QoS). For the above problems, firstly, the Gauss Markov mobility model is used to predict the position of the vehicle terminal at the next moment, and the candidate network set that meets the terminal service quality is selected to make the intersection with the current candidate network set. Secondly, if the current access network is not in the intersection, the variable-step firefly algorithm is used to find the best network. Thirdly, the terminal that fails to switch due to the prediction error is migrated to the macro cellular to ensure the continuity of communication. Simulation results show that the proposed algorithm can reduce the frequent handoff phenomenon, such as ping pong handoff in the ultra-dense heterogeneous wireless network. Meanwhile, it can improve the user service quality and network throughput.
Key words:Ultra-heterogeneous network/
Handoff/
Quality of Service (QoS)/
Location prediction
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